Proceeding Report of the Trent Graduate Students in Science Symposium
Bibliographic record
Abstract
The Trent Graduate Students in Science (TGSS) Symposium took place on March 9th, 2019 in Otonabee College at Trent University (Figure 1) from 8:30 AM to 5:30 PM. The purpose of this meeting was to bring together graduate researchers in a variety of different scientific disciplines to discuss the most recent scientific discoveries at Trent University and topics relevant to graduate studies as well as to facilitate networking and the practicing of presentation skills. Keynote speakers Dr. Raymond March and Dr. Douglas Evans used their own experiences and research to give insight into graduate studies and Jayme Stabler led a workshop on being an effective teaching assistant. Graduate students presented orally in morning and afternoon sessions (Session 1 and Session 2) in two concurrent presentation rooms (A and B) as well as in a short poster and ePoster presentation session midday. A summary of the TGSS Symposium is included in Figure 2. To facilitate the exchange of information in a multidisciplinary fashion, students in various scientific disciplines were dispersed throughout the sessions rather than grouped together. Each oral, poster and ePoster presentation was judged by a minimum of two judges. Each oral, poster and ePoster presentation was judged by a minimum of two judges. There was a total of 70 attendees, which included 28 graduate student presenters, 9 presentation judges and/or keynote speakers, and 5 members of the organizing committee. The organizing committee comprised of Erika L. Crowley, Kelly Wright, Novin Nezamololama, Verena Sesin and Amanda Stubbs (Figure 3).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.072 | 0.023 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".